1. Field of the Invention
This invention relates to a highly efficient coding apparatus of image data which is applied to compress and encode the image data.
2. Description of the Prior Art
Various kinds of encoding systems utilizing the correlation of image signals have been proposed for reducing the number of bits in each pixel or picture element (sample) of the digitized image data. As disclosed in the specification of Japanese Patent Laid Open Publication (JP,A) No. 144989/1986, the applicant of the present invention has proposed a highly efficient coding apparatus in which a dynamic range equal to a difference between a maximum value and minimum value of a plurality of pixels included in a two-dimensional block, is obtained and the encoding adapted to the dynamic range is executed. On the other hand, as shown in the specification of Japanese Patent Laid Open Publication (JP,A) No. 92626/1987, there has been proposed a highly efficient coding apparatus in which the encoding adapted to the dynamic range is executed with respect to a three-dimensional block which is formed by pixels in a plurality of areas each belonging to a plurality of frames. Further, as disclosed in the specification of Japanese Patent Laid Open Publication (JP,A) No. 128621/1985, there is been proposed a variable length encoding method in which the number of bits changes in accordance with the dynamic range so that the maximum distortion, which occurs upon digitization, becomes constant.
The above encoding methods adapted to the dynamic range (hereinafter, ADRCs) relate to highly efficient coding methods whereby, the number of bits per pixel is reduced by using the fact that images have a strong correlation in a small area (block), which is obtained by dividing one picture plane. That is, the difference between the minimum or maximum value in the block and the level of each pixel becomes smaller than the original level. This difference can be digitized by a number of bits which is smaller than the number of original bits.
The present invention can be applied to the digitization of the level standardized by the minimum or maximum value in the foregoing ADRC. However, this invention is not limited to ADRC, but can be also applied to a digitizing circuit for expressing a digital image signal by a predetermined number of bits in a manner similar to the ADRC.
As shown in FIG. 1, in performing the digitization of two bits in ADRC, a dynamic range DR in a block as, which is a difference between the maximum value MAX and minimum value MIN, is uniformly divided into for level ranges. The value of the pixel from which the minimum value MIN was eliminated is expressed by a two bit digitization code corresponding to the respective level ranges. On the decoding side, one of the central decoding representative level, I0 to I3, in each level range is decoded from the dynamic range DR and the digitization code, and the minimum value MIN is added to the decoded value, so that the pixel data in the block is reconstructed.
FIG. 2 shows an example of the digitization performed in ADRC in which one block of a one dimensional ADRC is constructed by six pixels which are continuous in the horizontal direction. Data indicated by O denotes true values of the pixels in the block. A horizontal change, due to digitization, is indicated by a solid line 41. In the case where the encoding was executed by two bits ADRC, reconstruction levels indicated by X are obtained on the decoding side and a corresponding change in signal as shown by a broken line 42 occurs in the reconstructed image.
In the conventional digitization, the level of the original pixel is replaced with the nearest decoding representative level in order to minimize the digitization error and to improve the S/N ratio. However, there is a case where a visually conspicuous deterioration occurs in the reconstructed image even if the image is quantitatively good. For example, the original smooth horizontal change 41, as shown in FIG. 2, results in the rough change 42 after the reconstruction, that is, visually conspicuous noises are generated in the reconstructed image. These noises cause the snow noises, which occur in a received television image in a weak electric field, to be made fine and jitter-like. The occurence of such a problem results from the fact that when people recognize an image, they are sensitive to differentiating characteristics of the image.
FIG. 3 shows another example of digitization performed in ADRC, that is, shows a time change of pixels at positions belonging to six frames which are continuous in the time direction and spatially correspond to those frames. For simplicity, it is assured that each block in which the six pixels are included has the same maximum value MAX and the same minimum value MIN. The data shown by O denotes the true values of the pixels. The change in the time direction is shown by a solid line 141. In the case were the encoding was executed by two bit ADRC, the reconstruction level are shown by X which are obtained on the decoding side and a change in the signal as shown by a broken line 142 occurs in the reconstructed image.
In the example shown in FIG. 3, the original smooth change 141 in the time direction results in the rough change 142 after the reconstruction. Visually conspicuous noises are generated in the reconstructed image as in the example shown in FIG. 2.